Intel® Select Solutions for AI Inferencing v2

Intel® Select Solutions for AI Inferencing are turnkey platforms that provide pre-bundled, verified, and optimized solutions for low-latency, high throughput inference performed on a CPU, not on a separate accelerator card.

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Base and Plus Configurations for the Intel Select Solutions for AI Inferencing v2

Ingredient

Intel Select Solutions for AI Inferencing v2 Base Configuration

Intel Select Solutions for AI Inferencing v2 Plus Configuration

Number of Nodes

Single-node configuration

Single-node configuration

Processor

2 x Intel® Xeon® Gold 6248 processor (2.50 GHz, 20 cores, 40 threads), or a higher number Intel® Xeon® Scalable processor

2 x Intel® Xeon® Platinum 8268 processor (2.90 GHz, 24 cores, 48 threads), or a higher number Intel Xeon Scalable processor

Memory

192 GB or higher (12 x 16 GB 2,666 MHz DDR4 ECC RDIMM)

384 GB (12 x 32 GB 2,934 MHz DDR4 ECC RDIMM)

Boot Drive

1 x 256 GB Intel® SSD DC P4101 Series (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC) or higher

1 x 256 GB Intel SSD DC P4101 Series (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC) or higher

Storage

Data drive: 1.6 TB NVM Express* (NVMe*) Intel® SSD DC P4510 Series

Cache drive: 375 GB Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD

Data drive: 1.6 TB NVMe* Intel SSD DC P4510 Series

Cache drive: 375 GB Intel Optane SSD DC P4800X U.2 NVMe* SSD

Data Network

1 x Intel® Ethernet Converged Network Adapter (Intel® Ethernet CNA) XXV710-DA2 SFP28 DA Copper PCIe* x 8 dual-port 25/10/1 GbE

1 x Intel Ethernet Converged Network Adapter (Intel Ethernet CNA) XXV710-DA2 SFP28 DA Copper PCIe* x 8 dual-port 25/10/1 GbE

Management Network

Integrated 1 GbE port 0/RMM port

Integrated 1 GbE port 0/RMM port

Software

Linux OS

CentOS Linux release 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7

CentOS Linux release 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7

Intel® Math Kernel Library (Intel® MKL)

Intel Math Kernel Library (Intel MKL) version 2019 Update 4

Intel Math Kernel Library (Intel MKL) version 2019 Update 4

Intel® Distribution of OpenVINO™ Toolkit

2019 R1.0.1

2019 R1.0.1

OpenVINO™ Model Server

0.4

0.4

TensorFlow

1.14

1.14

PyTorch

1.2.0

1.2.0

MXNet

1.3.1

1.3.1

Intel® Distribution for Python*

2019 Update 1

2019 Update 1

Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN)

0.19 (implied by the OpenVINO™ toolkit)

0.19 (implied by the OpenVINO toolkit)

Deep Learning Reference Stack (DLRS)

v4.0

v4.0

Source-to-Image

1.1.14

1.1.14

Docker

18.09

18.09

Kubernetes

v1.15.3

v1.15.3

Kubeflow

v0.6.1

v0.6.1

Helm

2.14.3

2.14.3

Seldon Core

0.3.2

0.3.2

Ceph

v14.2.1

v14.2.1

Min.io (Rook v1.0)

RELEASE.2019-04-23T23-50-36Z

RELEASE.2019-04-23T23-50-36Z

Rook

1.0.5

1.0.5

Other

Trusted Platform Module (TPM)

TPM 2.0

TPM 2.0

Minimum Performance Standards

Verified to meet or exceed the following minimum performance capabilities:

Classification Using ResNet-50 on OpenVINO Toolkit

1,900 images per second (91 percent top-5 accuracy)

2,650 images per second (91 percent top-5 accuracy)

Scaling in Emulated Real-World Scenario from 1 Node to 2 Nodes Up to 1.91x1 Up to 1.91x2

Business Value of Choosing a Plus Configuration Over a Base Configuration

The Plus configuration provides up to 39 percent faster inferencing performance.1

**Recommended, not required

產品與效能資訊

1

Intel 在 2019 年 10 月 9 日進行的測試。測試組態:兩個節點,2 x Intel® Xeon® Gold 6248 處理器 (2.50 GHz,20 個核心,40 個執行緒),12 x 16 GB 2,666 MHz DDR4 ECC RDIMM (192 GB 總記憶體),開機磁碟機:1 x 256 GB Intel® SSD DC P4101 系列 (M.2 80 mm PCIe* 3.0 x4, 3D2,TLC),資料磁碟機:1.6 TB NVM Express* (NVMe*) Intel® SSD P4510 系列,快取磁碟機:375 GB Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD,資料網路:1 x 10Gb Intel® Ethernet Converged Network Adapter X722 (Intel® Ethernet CNA X722),管理網路:整合式 1 gigabit 乙太網路 (GbE) 連接埠 0/RMM 連接埠。軟體:CentOS* Linux 版本 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7,Intel® 數學核心程式 (Intel® MKL) 版本 2019 更新 4,Intel® Distribution of OpenVINO™ 工具組 2019 R1.0.1,OpenVINO™ 模型服務 0.4,Intel® Distribution for Python* 2019 更新 1,Intel® 深度神經網路數學核心程式 (Intel® MKL-DNN) 0.19,Deep Learning Reference Stack (DLRS) v4.0,Docker v18.09,Helm v2.14.3,Kubernetes v1.15.3,Kubeflow v0.6.1,Seldon Core v0.3.2,Rook v1.0.5,Ceph v14.2.1,Min.io (Rook v1.0) 版本。2019-04-23T23-50-36Z。模擬真實場景中縮放比例—輸送量測試:標準化效能 1 (Intel® 超執行緒技術 (Intel® HT 技術):關閉)。

2

Intel 在 2019 年 10 月 9 日進行的測試。測試組態:兩個節點,2 x Intel® Xeon® Platinum 8268 處理器 (2.90 GHz,24 核心,48 執行緒),12 x 16 GB 2,666 MHz DDR4 ECC RDIMM (192 GB 總記憶體),開機磁碟機:1 x 256 GB Intel® SSD DC P4101 系列 (M.2 80 mm PCIe* 3.0 x4,3D2,TLC),資料磁碟機:1.6 TB NVM Express* (NVMe*) Intel® SSD P4510 系列,快取磁碟機:375 GB Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD,資料網路:1 x 10Gb Intel® Ethernet Converged Network Adapter X722 (Intel® Ethernet CNA X722),管理網路:整合式 1 gigabit 乙太網路 (GbE) 連接埠 0/RMM 連接埠。軟體:CentOS* Linux 版本 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7,Intel® 數學核心程式 (Intel® MKL) 版本 2019 更新 4,Intel® Distribution of OpenVINO™ 工具組 2019 R1.0.1,OpenVINO™ 模型服務 0.4,Intel® Distribution for Python* 2019 更新 1,Intel® 深度神經網路數學核心程式 (Intel® MKL-DNN) 0.19,Deep Learning Reference Stack (DLRS) v4.0,Docker v18.09,Helm v2.14.3,Kubernetes v1.15.3,Kubeflow v0.6.1,Seldon Core v0.3.2,Rook v1.0.5,Ceph v14.2.1,Min.io (Rook v1.0) 版本。2019-04-23T23-50-36Z。模擬真實場景中縮放比例—輸送量測試:標準化效能 1.91 (Intel® 超執行緒技術 (Intel® HT 技術):關閉)。